Recruiting

AI in Outpatient

Sponsor:

Mayo Clinic

Code:

NCT06580158

Conditions

Aortic Stenosis

Diastolic Dysfunction

Eligibility Criteria

Sex: All

Age: 60+

Healthy Volunteers: Not accepted

Interventions

AI-ECG Dashboard

Point of care ultrasound (POCUS)

Study Details

Brief summary:

Two recently developed artificial intelligence-enabled electrocardiogram (AI-ECG) models have been developed to detect aortic stenosis (AS) and diastolic dysfunction (DD). AI-ECG for AS has a sensitivity of 78% and specificity of 74%, and AI-ECG for DD has a sensitivity of 83% and specificity of 80%. However, these models have never been prospectively applied to diagnose AS or DD, which may be useful for patients and providers from a diagnostic and prognostic perspective and especially in settings where access to higher- level medical care is limited. In this study, we aim to determine the clinical utility of these AI-ECG models by prospectively applying them to an outpatient cohort and then completing a focused point-of-care ultrasound to evaluate those who are AI-ECG positive for AS and DD.

Conditions

Aortic Stenosis

Diastolic Dysfunction

Study ID

NCT06580158

Start date

Nov 8, 2024

Status verified date

Jan, 2026

Completion date

Mar, 2027

Anticipated

Primary completion date

Mar, 2027

Anticipated

Eligibility Criteria

Eligibility Criteria

Sex: All

Age: 60+

Healthy Volunteers: Not accepted

Inclusion Criteria:

  • ≥ 60 years of age must have a clinical scheduled ECG performed.

Exclusion Criteria:

  • < 59 years of age
  • Is not scheduled for a clinical ECG
  • Unable to provide consent.

Study Design

Enrollment

2000 participants

Anticipated

Interventions and Outcome Measures

Arms

Patients who are completing an outpatient electrocardiogram (ECG) at the Mayo Clinic.

Interventions

AI-ECG Dashboard

Patients standard of care ECG's will be processed through the AI-ECG Dashboard

Point of care ultrasound (POCUS)

Patients will undergo a ultrasound to confirm diagnosis of atrial stenosis or diastolic dysfunction.

Primary outcome measure

  • Number of patients with positive AI-ECG [ Time Frame: Baseline ]
  • Number of studies with reasonable image quality in patients with positive AI-ECG [ Time Frame: Baseline ]

Central Contacts and Locations

Central contacts

Brian Rudquist

(507) 538-5146Rudquist.Brian@mayo.edu

Jae Oh, M.D.

oh.jae@mayo.edu

Locations

Mayo Clinic

Recruiting

Rochester, Minnesota, United States, 55905

Contacts

Jae Oh, M.D.

oh.jae@mayo.edu

More Information

Sponsor

Mayo Clinic

Last update posted

Mar 4, 2026

Last verified

Jan, 2026

Trial information was received from ClinicalTrials.gov and was last updated on 2026-09-10. This information was provided to ClinicalTrials.gov by Mayo Clinic on 2026-03-04.